The Database Research and Integration Group is developing methods for large-scale analysis and constructing the systems that link everyone together. Novel distance measures, index structures, search algorithms, mining techniques, and a retinal cell atlas make it possible to handle the scale and complexity of the data. These techniques and those developed by other groups are integrated into BISQUE, a database system that serves as a central repository for images and helps biologists with image capture, analysis, and querying.

Accurate tracking of the microtubules is crucial for their dynamic instability analysis. We present a method for microtubule tracking that employs an arc-emission Hidden Markov Model (HMM) [1]. Proposed method is generic in terms of tracking general curvilinear structures/open-contour that can grow, shrink and undergo lateral motion from frame to frame.

The algorithm encodes the shape information of the structure in a spatially deformable trellis model that is iteratively modified to account for observations in subsequent frames. As the open contour is determined on the trellis of an HMM, a dynamic programming procedure reduces the computational complexity to linear in the length of the structure (or open-contour). Length changes of the structures are modeled by the addition of appropriate transient and absorbing states to the HMM. 

Our results provide experimental evidence for the proposed algorithm's capability to track non-rigid curvilinear objects in challenging environments in terms of noise and clutter.

Output of the proposed algorithm (green) and the ground truth (red).

[1] M.E. Sargin, A. Altinok, K. Rose, B.S. Manjunath, "Deformable Trellis: Open Contour Tracking in Bio-Image Sequences", IEEE Int. Conf. on Acoustics, Speech and Signal Processing (ICASSP'08), April 2008

Adopted from: http://micro.magnet.fsu.edu/cells/microtubules/microtubules.html

The Microtubule Dynamics and Motility Tools are used by researchers who try to understand the mechanisms of growing and shortening dynamics of microtubules (MTs) and related regulatory mechanisms associated with MTs functioning. MTs represent major structural components of the cytoskeleton that are involved in many cellular functions, especially in mitosis, cytokinesis (cell motility) and vesicular transport. They are assembled from heterodimers made of a GTP-bound forms of a-tubulin and b-tubulin proteins (Fig. 1). Uni-directional orientation of tubulin heterodimers in MTs results in polarized nature of MTs with a-tubulin exposed ends (called (-)-ends) being relatively stable ones and b-tubulin exposed end (called (+)-ends) being more unstable. Upon MT assembly, most of tubulin-bound GTP (with exception of subunits at the very ends of MTs) is hydrolyzed into GDP. The energy released by the hydrolysis of GTP to GDP results in decreased stability of MTs and leads to growing and shortening phase transitions at the microtubule ends (called dynamic instability). In addition, at the polymer mass steady state the growing and shortening transitions at (+)-end of a microtubule give rise to net growing, while the growing and shortening transitions at the opposite (-)-end of the microtubule gives rise to net shortening. This directional growth of MTs called treadmilling or flux. MTs also have a number of microtubule-associated proteins (MAPs) associated with their surfaces and ends. MAPs main functions are to regulate the polymerization dynamics of the microtubules and to mediate the functional interactions of microtubules with other cell components. Another class of proteins associated with MTs are motor proteins (kinesins and dyneins) responsible for directional transport of cargo vesicles. Proper dynamics of MTs required for normal cell functioning while aberrant behavior of MTs can lead to cellular dysfunction and/or death. Correspondingly, dynamics of MTs as well as associated with MTs cell signaling pathways are important targets for novel anti-cancer and anti- neurodegenerative therapies.

Biological images are critical components for a detailed understanding of the structure and functioning of cells and proteins. Image processing and analysis tools increasingly play a significant role in better harvesting this vast amount of data, most of which is currently analyzed manually and qualitatively. A number of image analysis tools have been proposed to automatically extract the image information. As the studies relying on image analysis tools have become widespread, the validation of these methods, in particular, segmentation methods, has become more critical. There have been very few efforts at creating benchmark datasets in the context of subcellular, cell and tissue imaging...

Tracing of curvilinear structures is one of the fundamental tools in the quantitative analysis of biological images, for extracting information about structures such as blood vessels and microtubules, and similar entities. Microtubules are tubulin polymer structures in cell bodies which are crucial in the mitosis, intra-cell transportation, and are a component of the cell's cytoskeleton. Researchers believe microtubules play a important role in Alzheimer's and in certain cancers. Presently, biologists are studying how these structures grow and shorten in the presence of certain key proteins such as Tau and with various drugs in the hope of understanding how they contribute to these diseases. The measurements of these microtubules with current techniques are very labor intensive. Therefore, automatic algorithms which will ideally trace microtubules with minimal human input are suited. Due to the limitations in biological sample preparation and fluorescence imaging, typical images in live cell studies exhibit severe noise and considerable clutter and automatic microtubule tracing becomes an hard task An automatic method has been proposed in in [1] for extracting curvilinear structures from live cell fluorescence images, but before biologists adopt new automated tracing algorithms, the performance has to be proven. We propose an evaluation method to compare the tracing results to ground truth data. The groun truth manually obtained from different experts is available for downloading.

The Microtubule Research Group is trying to understand how the essential growing and shortening dynamics of microtubules are regulated, and how proper regulation leads to normal cell biology while aberrant regulation can lead to cellular disfunction in cancerous and neurodegenerative conditions such as Alzheimer's disease. In addition to light microscopy level resolution, attempts to understand the precise molecular mechanisms regulating microtubule dynamics are also being conducted using atomic force microscopy.